Author(s)

Fred Viole¹, David Nawrocki²

¹OVVO Financial Systems, Holmdel, NJ, USA.
²Villanova School of Business, Villanova University, Villanova, PA, USA.

Minimizing the classical definition of risk should be a counterintuitive venture as the explanatory nature of historical metrics’ construction challenges their ability to serve a predictive purpose on a non-stationary process. We uncover an ill-conceived bias in these metrics and discover that they provide a contrary indication to an investment’s survivability. The breakdown in the explanatory-predictive link is troubling and we aim to correct this via a better derived explanatory metric. The predictive variant of our metric will directly question the notion of optimization in order to serve the first priority of any continuous system, survival.

Partial Moments, Asymmetric Nonlinear Utility, Entropy, Non-Stationary Benchmark

Viole, F. and Nawrocki, D. (2016) Predicting Risk/Return Performance Using Upper Partial Moment/Lower Partial Moment Metrics. Journal of Mathematical Finance, 6, 900-920. doi: 10.4236/jmf.2016.65060.